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Record W2052440692 · doi:10.1080/10934529.2010.513292

Surface-modified activated carbon with β-cyclodextrin—Part II. Adsorption properties

2010· article· en· W2052440692 on OpenAlexaff
Jae H. Kwon, Lee D. Wilson

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSorptionActivated carbonLangmuir adsorption modelAdsorptionBET theoryLangmuirNuclear chemistryAqueous solutionChemistryNitrogenMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Sorption properties of surface modified activated carbon (AC) with p-nitrophenol (PNP) and methylene blue (MB) in aqueous solution were investigated. The calculated surface areas for AC and surface modified AC were compared using nitrogen sorption and a dye-based method. The surface areas of AC and the surface modified AC with glutaraldehyde (AC-β-CD) (1:10:10⁹) and 1,4-phenylene diisocyanate (ACPDICD) measured by nitrogen sorption were 1,269 m²/g, 103 m²/g, and 95 m²/g, respectively (Langmuir model) and 956 m²/g, 74 m²/g, and 69 m²/g (BET model), respectively. However, the calculated surface areas for the dye-based method (PNP; pH 6.00) for AC, AC-β-CD(1:10:10⁹), and ACPDICD was 1,035 m²/g, 814 m²/g, and 76 m²/g (Langmuir model), respectively and 1,491 m²/g, 1,669 m²/g, and 92 m²/g (BET model), respectively. The corresponding surface areas for the dye-based method (MB; pH 8.40) for AC-β-CD(1:10:10⁹) and ACPDICD was 263 m²/g and 171 m²/g (Langmuir model), respectively and 1019 m²/g and 182 m²/g (BET model), respectively. The sorption capacity (Q(m)) and binding affinity characteristics [K(F)(L/g), K(L)(g/mol), and K(BET)(L/g)] were estimated at room temperature at equilibrium conditions using several sorption isotherm models.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.255
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2010
Admission routes1
Has abstractyes

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